Biography
Richard Paap is a professor of Econometrics at Econometric Institute, Erasmus School of Economics (ESE). He obtained his PhD from the same school in 1997. His research concerns the application of econometric models in marketing and macroeconomics using Bayesian and frequentist approaches. He has publications in several major econometric, economic and marketing journals and he is coauthor of the book Quantitative Models in Marketing Research. He is currently Academic Director of the Master Econometrics.
More information
Work
- Dennis Fok & Richard Paap (2025) - New misspecification tests for multinomial logit models - Journal of Choice Modelling, 54 - doi: 10.1016/j.jocm.2024.100531 - [link]
- Didier Nibbering & Richard Paap (2024) - Forecasting carbon emissions using asymmetric grouping - Journal of Forecasting, 43 (6), 2228-2256 - doi: 10.1002/for.3124 - [link]
- C (Cem) Cakmakli, Richard Paap & Dick van Dijk (2022) - Modeling and estimation of synchronization in size-sorted portfolio returns - Central Bank Review, 22 (4), 129-140 - doi: 10.1016/j.cbrev.2022.11.001
- Wendun Wang, X (Xiaoxue) Zhang & Richard Paap (2019) - To pool or not to pool: What i?s a good strategy for parameter estimation and forecasting in panel regressions? - Journal of Applied Econometrics, 34 (5), 724-745 - doi: 10.1002/jae.2696 - [link]
- Dennis Fok & Richard Paap (2019) - New Misspecification Tests for Multinomial Logit Models - [link]
- D Nibbering & Richard Paap (2019) - Panel Forecasting with Asymmetric Grouping - [link]
- Wendun Wang, X Zhang & Richard Paap (2019) - To pool or not to pool: What is a good strategy for parameter estimation and forecasting in panel regressions - [link]
- Koen Bel, Dennis Fok & Richard Paap (2018) - Parameter Estimation in Multivariate Logit Models with Many Binary Choices - Econometric Reviews, 37 (5), 534-550 - doi: 10.1080/07474938.2015.1093780 - [link]
- D Nibbering, Richard Paap & Michel van der Wel (2018) - What do professional forecasters actually predict? - International Journal of Forecasting, 34 (2), 288-311 - doi: 10.1016/j.ijforecast.2017.12.004 - [link]
- Philip Hans Franses, R (Rianne) Legerstee & Richard Paap (2017) - Estimating loss functions of experts - Applied Economics, 49 (4), 386-396 - doi: 10.1080/00036846.2016.1197373 - [link]
- Koen Bel & Richard Paap (2016) - Modeling the Impact of Forecast-based Regime Switches on US Inflation - International Journal of Forecasting, 32 (4), 1306-1316 - doi: 10.1016/j.ijforecast.2016.06.002
- Jean Marie Viaene, Irena Mikolajun, Richard Paap & O Zelenko (2016) - Trade Policy Options for Ukraine: East or West
- CJ Silva Lourenco, E Gijsbrechts & Richard Paap (2015) - The Impact of Category Prices on Store Price Image Formation: An Empirical Analysis - Journal of Marketing Research, 52 (2), 200-216 - doi: 10.1509/jmr.11.0536
- Koen Bel & Richard Paap (2014) - A Multivariate Model for Multinomial Choices
- Dennis Fok, Richard Paap & Philip Hans Franses (2014) - Incorporating Responsiveness to Marketing Effort in Brand Choice Modeling - Econometrics, 2 (1), 20-44 - doi: 10.3390/econometrics2010020
- Dennis Fok, Richard Paap & Philip Hans Franses (2014) - Incorporating Responsiveness to Marketing Efforts in Brand Choice Modeling
- Koen Bel, Dennis Fok & Richard Paap (2014) - Parameter Estimation in Multivariate Logit Models with Many Binary Choices
- Sjoerd van den Hauwe, Richard Paap & Dick van Dijk (2013) - Bayesian forecasting of federal funds target rate decisions - Journal of Macroeconomics, 37, 19-40 - doi: 10.1016/j.jmacro.2013.05.001 - [link]
- Sjoerd van den Hauwe, Richard Paap & Dick van Dijk (2013) - Bayesian forecasting of federal funds target rate decisions
Erasmus Q Intelligence
- Start date approval
- november 2022
- End date approval
- november 2025
- Place
- ROTTERDAM
- Description
- Consultancy voor EQI (Erasmus BV)
Econometrics 1
- Year
- 2024
- Course Code
- FEB22004
Econometrics 1
- Year
- 2024
- Course Code
- FEB22004X
Bayesian Econometrics
- Level
- Master
- Year Level
- Master
- Year
- 2024
- Course Code
- TIF20117
Bayesian Econometrics
- Year
- 2024
- Course Code
- FEM21026
Bayesian Econometrics in Finance
- Year
- 2024
- Course Code
- FEM21032
